Original
Presence and predictors of suicide ideation in a clinical outpatient context
Elena Huguet Cuadrado(a,b, Ignacio Fernández-Arias(b, Cristina Larroy García(b
a) Psychology department, European University of Madrid, Madrid, Spain
b) Personality, assesment and clinical psychology, Complutense University of Madrid, Madrid, Spain
Ansiedad y Estrés, (2023), 29(1), 10-17
https://doi.org/10.5093/anyes2023a2
https://www.ansiedadyestres.es
Bibliography reference
INFO ARTICLE
Received 7 April 2022
Accepted 27 June 2022
Available online 20 July 2022
ABSTRACT
Abstract: Background: It is of vital importance to study the risk factors associated with suicidal behaviour. The purpose of this study is to analyse the presence of suicide ideation and related factors in an applied clinical environment. Method: A correlative-predictive study is conducted with a sample of 180 adult patients, 64% women, with an average age of 31.88 (SD = 14.473) at the University Psychology Clinic of Universidad Complutense of Madrid. Suicide ideation is analysed (measured by Item 9 of the BDI-II), together with its relationship with clinical diagnosis, symptoms of depression, hopelessness and a range of sociodemographic variables. Results: 31.7% of the sample had shown suicide ideation. Significant differences were found depending on: cohabitation unit, symptoms of depression, presence of hopelessness, personal history and being under pharmacological treatment. Living alone is postulated as a stable predictor of suicide ideation (with an OR of 0.403). Together with personal history, symptoms of depression and hopelessness, these factors explain 42.5% of the presence of suicide ideation (?2(13) = 65.056; p < .001; R2 = 0.425). Conclusions: The high prevalence of suicide ideation in the clinical population and the risk factors found, confirm the importance of focusing on this phenomenon, in particular taking into account its presence within different problems beyond the diagnostic label and the significance in certain contextual factors (e.g., living alone).
KEYWORDS
Suicidal ideation
Risk factors
Depression
Hopelessness
Personal history
Presencia y predictores de la ideación suicida en contexto clínico ambulatorio
Ansiedad y Estrés, (2023), 29(1), 10-17
https://doi.org/10.5093/anyes2023a2
https://www.ansiedadyestres.es
Bibliography reference
RESUMEN
Antecedentes: El estudio sobre los factores de riesgo asociados a la conducta suicida es primordial debido al alarmante aumento de suicidios consumados en España en estos últimos años. El objetivo de este estudio es analizar la presencia de ideación suicida y factores relacionados con ésta, tanto sociodemográficos como clínicos. Método: Se realiza un estudio descriptivo, correlacional, transversal y retrospectivo con una muestra de 180 pacientes mayores de edad de la Clínica Universitaria de Psicología de la Universidad Complutense de Madrid. Se analiza la ideación suicida (medida a través del ítem 9 del BDI-II), su relación con el diagnóstico clínico, la sintomatología depresiva, la desesperanza y diversas variables sociodemográficas. Resultados: Un 31,7% de la muestra presentó ideación suicida. Se encontraron diferencias significativas dependiendo de: núcleo de convivencia, sintomatología depresiva, presencia de desesperanza, antecedentes personales y estar bajo tratamiento farmacológico. Vivir solo, tener antecedentes personales, sintomatología depresiva y desesperanza fueron predictores estadísticamente significativos de la aparición de ideación suicida (? 2 (13) = 65, 056; p < 0,001; R 2 = 0,425). Conclusiones: La alta prevalencia en población clínica y los factores de riesgo encontrados confirman la importancia de prestar atención a este fenómeno, sobre todo teniendo en cuenta el elevado porcentaje de ideación en diferentes problemáticas más allá de la etiqueta diagnóstica.
PALABRAS CLAVE
Ideación suicida
Factores de riesgo
Depresión
Desesperanza
Antecedentes personales
Introduction
Suicide has emerged as the main cause of non-natural death within Spanish society (Spanish National Statistical Institute, 2020). There is a clear increase in social alarm and call for public policies to prevent suicide and to detect and treat people at risk. Epidemiological data indicate a progressive increase in cases of suicide among women, while cases among men remain stable (Cayuela et al., 2018), as well as an exponential increase in the adolescents (ANAR Foundation, 2021).
One essential source of information to explore the problem in greater depth involves analyzing the characteristics and circumstances of people who take their own life through an act of suicide (Al-Halabí & Fonseca-Pedrero, 2021). In this regard, forensic sources and national statistics are of great use, but only partially and inadequately. The study of suicidal behaviour must not solely address the act of suicide, but instead begin at the point when a person considers taking their own life. Suicidal morbidity covers passive suicide ideation (or wishing one were dead), active suicide ideation, the planning process, and the suicide attempt itself (Ayuso et al., 2012; Posner et al., 2011). All categories are part of the suicide continuum, and these categories have an increasing relationship with the risk of suicide (De Wilde et al., 1996).
The ESEMeD study (Gabilondo et al., 2007) into psychiatric epidemiology in the general population found that 4.4% of people in Spain will consider suicide at least once during their lifetime; 1.4% will just plan and 1.5% will attempt suicide. These figures which coincide with other studies of the Spanish population in general (Cabello et al., 2020; Ramírez, 2015). Among individuals with suicide ideation, the conditional probability of making an attempt, after having considered a plan, was far higher (73%) than among those who had no plan (14.4%), confirming the idea of an autolytic continuum.
Multiple studies have analysed the characteristics of individuals with a presence of suicidal ideation and/or behaviour. From a socio-demographic perspective, risk factors identified include age (middle age and youth; Baca-García et al., 2010; Cabello et al., 2020); gender (women have higher rates of ideation and attempts; Bello & Teruel, 2020) and level of education (lower level of education being associated with greater risk of suicide; Lorant et al., 2005). Contextual risk factors exist, such as a lack of social support or the presence of environmental stress factors (Kaslow et al, 2005; Li et al., 2011).
More decisively, suicidal behaviour has been associated with the presence of psychopathology, mainly in affective disorders, substance abuse, personality disorders and psychotic disorders (Burr et al., 2018; Holman & Williams, 2020; Ribeiro et al., 2016). Lastly, hopelessness is one of the most studied clinical risk factors because of its strong relationship to depression and suicidal behaviour (Antón-San-Martin et al., 2013; Bagge et al., 2014; Klonsky & May, 2015), this being a key vulnerability factor for the evolution from passive ideas to active suicide ideation (Joiner, 2007; Van Orden et al., 2010).
Although most studies take the general population as their frame of reference, the presence of suicide ideation is particularly common when people reveal psychological problems and/or stressful life experiences (De Beurs et al., 2019). This suggests that applied healthcare contexts (Dougherty et al., 2004) rather than specific units (such as acute units or borderline personality disorder units; Antón-San-Martin et al., 2013; Bonet et al., 2019; Pacheco, 2016; Ramírez, 2015) would be an ideal environment in which to approach the study of this phenomenon. However, there are few studies that aim to characterise the phenomenon in clinical population treated in a natural environment. Focusing on the natural environment gives us the opportunity to quantify the presence of suicide ideation, while identifying associated characteristics that could be interpreted as protective or risk factors. The latter are particularly important given their interaction, increasing the estimated risks, and it would therefore seem essential to approach the phenomenon through models that cover potential modulating factors as a whole (Franklin et al., 2017).
In accordance with the above, the purpose of this study is to quantify the presence of suicide ideation among people requesting psychological care at an outpatient clinic, and to establish a predictive model for such ideation that takes into account socio-demographic and clinical factors.
Hypothesis
The hypotheses that were tested, based on the scientific literature reviewed and the general objectives described above, are:
- There will be a prevalence above 15% (Beck et al., 1993; Gabilondo et al., 2007) of suicidal ideation among patients in a clinical care context.
- Suicidal ideation will be more prevalent in women.
- Patients with mood disorders will present more suicidal ideation compared to other diagnostic categories.
- There will be a positive relationship between the presence of suicidal ideation and depressive symptomatology, regardless of diagnosis.
Method
Participants:
The sample is incidental and for this purpose the clinical records from the archive of the University Psychology Clinic of Complutense University of Madrid (CUP-UCM) were used. Due to the nature of a clinical records review, the inclusion criteria were broad. These were: being patients of legal age at the time of data collection, complete accessibility to patient clinical records from the CUP-UCM archive and the complete availability of the clinical report made by the therapist as well as the quantitative data from the psychometric test used in the assessment.
The sample finally consisted of 180 patients, of legal age, that requested general psychological care relating to different problems between January 2015 and December 2016, as December 23 was considered the deadline for data collection.
As may be seen in Table 1, most of the participants were women (64.4%), single (55.6%), adults, aged between 18 and 73 years of age, with a mean age of 31.88 years (SD=14.473). 53.9% of the participants were studying, and 25.5% were in active employment; 32.8% had a university qualification, and most of them lived in company (88.9%).
Evaluation procedure:
The data were drawn from the clinical records of the centre. The evaluations were conducted by specifically trained and qualified psychologists; each of the therapists (12 therapist overall between January 2015 and December 2016) had a specific master´s degree accrediting their specialization in the assessment, diagnosis, and treatment of psychological disorders. As mentioned above, all the participants completed their individual assessment process at the clinic.
Socio-demographic and clinical variables
Information was gathered regarding gender, age, marital status, level of education, occupational situation and cohabitation unit, employing an ad hoc questionnaire. This same questionnaire gathered information regarding the following clinical variables: family history (if there were previous psychological diagnosis in their nuclear family), personal history (if there were previous psychological diagnosis, reflected in psychological reports provided by the patients or to have completed the psychological assessment process and initiated psychological treatment), consumption of psychopharmaceuticals at the time of the evaluation and, finally, the main or primary diagnosis was also recorded according to DMS-5 criteria.
This diagnosis was assessed based on the clinical judgment of the therapist, after the evaluation process, which included semi-structured interviews and validated and reliable questionnaires for this purpose. and it was also based on compliance with the diagnostic criteria proposed by the DSM-5 (Morán, 2014). This was divided into four main categories: (1) no diagnosis (criteria not fulfilled for any category); (2) diagnosis related to depressive disorders; (3) diagnosis related to anxiety disorders, and (4) other specific diagnoses.
Suicide ideation and symptoms of depression.
Suicide ideation was evaluated by Item 9 on the Beck Depression Inventory II (BDI-II) by Beck et al. (1996), in the version adapted for the Spanish population (Sanz & García-Vera, 2013), which evaluates autolytic thoughts over the past two weeks. The use of this item as a suicide ideation index is recommended, as it is effective at screening and predicting completed and attempted suicides (Pelizza et al., 2020; Hom et al., 2018). It comprises four levels, which in this study were dichotomised into absence of suicide ideation (level 0) and presence of suicide ideation (levels 1, 2 and 3) (Taylor et al., 2015).
Depression symptoms were assessed as well using BDI-II (Sanz & García-Vera, 2013) without the punctuation on Item 9, as was developed in previous research (Jongkind et al., 2019) with a high-level internal consistency (.91). The present study used the self-report 21-item version. This inventory reveals a test-retest reliability ranging from .60 to .62, with an acceptable internal consistency (.83).
Since much of the literature recommends taking hopelessness into account as a fundamental process in a proper approach to the phenomenon of suicide, Item 2 (pessimism) of the BDI-II was analysed separately, as it reveals an adequate convergent measurement (r = 0.64, p < 0.01) with the Beck Hopelessness Scale (Beck et al., 1974), as indicated in the study by Toro-Tobar et al. (2016).
Ethical considerations
All patients attending were informed and received the informed consent form in which the research purposes of the data collection are made explicit. In addition, CUP-UCM has a research department, in which the management assesses, approves, and supervises the studies carried out at the clinic. Ethical standards were met in the treatment of anonymization and confidentiality data in the use of research databases in accordance with the Organic Law 3/2018 on Personal Data Protection and guarantee of digital rights (LOPD-GDD) and the latest updated version of the Helsinki declaration (2013).
Data analysis:
The data were processed by means of the statistical package SPSS v25. Descriptive statistics were used to characterise the sample at the socio-demographic and clinical levels. To detect significant differences in these variables depending on the presence or absence of suicide ideation, bivariate contrasts were performed (?2 for the categorical variables and t for the continuous variables) and Cohen's d was calculated as well to estimate effect sizes (Cohen, 1988).
In addition, the multicollinearity of the variables was checked by Tolerance and IVF (Variance Inflation Factor) tests, which allows us to describe the multicollinearity existing among the variables, since this could increase the variance of the regression. It is generally accepted to consider that problems associated with strong collinearity start with tolerances less than .10 and values greater than 10 are usually accompanied by problems associated with excessive collinearity (Pardo Merino & Ruiz, 2015).
Lastly, a stratified binary logistical regression was performed in order to identify socio-demographic and clinical predictors of suicide ideation, controlling for possible co-variations between them. The stratification was performed in accordance with the following models: Model 1: gender, age, marital status, education, occupation, cohabitation unit, personal history, family history and consumption of psychopharmaceuticals; Model 2: Model 1 + symptoms of depression and hopelessness; Model 3: Model 2 + re-codified diagnosis. Categorial variables we transformed into dummy variables, binary values that take a value of 0 (absence) and 1 (presence), in order to include them in the regression model. In those independent categorical variables composed of more than two categories (marital status and diagnosis), they were recoded into indicator variables or dummies for each category (Berlanga Silvente, & Vilà Baños, 2014) and they were automatically made by SPSS. The odds ratio was interpreted based on the Exp (B) (Ranganathan et al., 2017) and, to facilitate interpretation, if Exp (B) was lower than 1, the value was transformed into 1/ExpB (Pardo Merino & Ruiz, 2015).
Results
50% of the sample revealed a family or personal history of psychological diagnosis, most were under pharmacological treatment (63.9%), and following the conclusion of the evaluation interviews, only 15.6% had no diagnosis. 16.7% revealed a diagnosis of depression, 33.9% an anxiety-type disorder (general anxiety disorder, obsessive-compulsive, specific phobia, post-traumatic stress…) and 33.9% were diagnosed with some other non-depressive psychological disorder (Table 1).
Regarding clinical variables, the descriptive analyses showed that the mean for symptoms of depression measured by total BDI-II was 22.39 (SD = 12.588). Referring to Item 9 of the BDI-II, 68.3% of the sample made no mention of suicidal ideation. The prevalence of any type of suicide ideation was 31.7%. Of this 31.7%, 0.6% suffered very severe suicide ideation, another 0.6% severe suicide ideation, and 98.8% mild suicide ideation.
Table 2 compares the socio-demographic characteristics depending on whether the participants reveal any type of ideation. No evidence was found of significant differences in any variable except for the cohabitation unit within the same home, with more than 50% of those living alone having suicide ideation, compared with 28.7% of those suffering such ideation and living in company (?2(1) = 5.661; p = .017).
However, as was expected, the level of symptoms of depression (BDI-II without Item 2 and 9), (t(178)= -6.799; p < .001; d = 1.076) and hopelessness (?2(1) = 23.276; p < .001) of those patients with some type of ideation is significantly higher than those suffering no such ideation. Size effect in BDI-II is considered high according to Cohen´s (1980) since d is above .80. Lastly, those that expressed ideation reveal more personal history (?2(1) = 13.997; p < .001) and a higher percentage were under pharmacological treatment (?2(1) = 6.121; p = .013)
No collinearity was observed between the factors, as the tolerance values were above .1 for each of the variables considered and the values of the Variance Inflation Factor (VIF) were below 10.
Table 5 shows a predictive model based on a stratified regression analysis. The first model, which included clinical and socio-demographic variables, revealed that living alone was a significant predictor (ß = 1.395; p = .018; OR = 4.035), increasing the probability of suicide ideation being present by 4 times (OR = 4.035). The presence of a personal history likewise proved significant (ß = 1.134; p = .003) with an OR of 3.1 regarding the presence of ideation. This model explained 19.5% of the variance (?2(11) = 26.97; R2 = .195). The second model, which maintained the previous variables and included the presence of symptoms of depression (BDI-II without Items 2 and 9) and presence of hopelessness (Item 2), revealed an increase in predictive power, which represented 42.5% of variance (?2(13) = 65.056; R2 = .425). Symptoms of depression proved a significant predictor (ß = 0.088; p < .001; OR = 1.092) representing an increase of 2.4 times the probability of suicide ideation for every 10-point increase in the mean value for symptoms of depression (calculated on the basis of e kß). However, upon examination, the presence of hopelessness also was significant (ß = 1.242; p = .012), increasing the probability of suicide ideation by 3.46 times. Living alone continued to be a significant predictor (ß = -1.553; p = .027), multiplying the probability of ideation by 4.72 times (OR = 4.72). The presence of personal history likewise remained a significant predictor (ß = 0.987; p = .021) with an OR of 2.68.
Lastly, Model 3, including all the above variables plus diagnosis, did not provide evidence of any significant increase compared with Model 2 (?2(3) = 3.216; p = .360; R2 = .443), with the variance explained remaining at 44.3%. Diagnosis therefore did not prove to be a significant predictor. Symptoms of depression (ß = 0.093; p < .001), the presence of hopelessness (ß = 1.252; p = .014), the presence of a personal history (ß = 0.984; p = .023) and living alone (ß = -1.739; p = .016) remained significant predictors, irrespective of the diagnosis.
Discussion
The purpose of this study is to analyse the presence of suicide ideation in an applied context, and to identify predicting factors. Following an analysis of the data from 180 participants, it was found that 31.7% of the sample revealed some type of suicide ideation, mainly non-specific suicidal ideation. As expected, this figure is higher than the one obtained in epidemiological studies that take the general population as their frame of reference (Bernardi et al., 2019; Miret et al., 2014; Mortier et al., 2021). It would be expected that those attending a specialist centre would reveal high levels of dysphoria, a factor connected with the presence of suicide ideation. Various studies have specifically emphasised the high rates of suicide ideation among clinical populations (Bryan et al., 2012; Le et al., 2021; Nock et al., 2009), which is consistent with the evidence revealed by this work. However, most of the reference literature focuses on populations with acute autolytic attempts or patients that come from specialist units; perhaps this last factor provides a potential reason behind the fact that ideation found was nonspecific/mild and not severe: because of the type of generalist psychological assistance service received, oriented to the general non-hospitalized population rather than the psychiatric or hospitalized population. Unlike previous studies, this work focuses on a sample of patients with a wide range of psychological problems, being treated within a natural and general clinical context. As indicated by Labrador et al. (2010), this type of sample is similar and analogous to those found within other general mental health and even primary care units (see Díaz et al., 2017; García-Pedrajas et al., 2018). It is significant that practically one in every three people requesting psychological care reveals some type of suicide ideation. The fact that a minimal percentage show systematised and action-focused ideation, and that most patients with suicide ideation indicate that at present they would not make any attempt, does not undermine the importance of the figure. According to the continuous model of Klonsky et al. (2016), this type of ideation is the precursor to attempted suicide, and the proper identification, prevention and treatment of suicide ideation in the initial stages must therefore be prioritised, especially when such initial forms are so frequent.
In identifying predictors, no evidence was found of any gender difference in terms of whether or not suicide ideation is present, although the presence is slightly higher in women. This finding contrasts with much of the literature, indicating a significantly greater presence of ideation among women (Assari & Lankarani, 2016; Husky et al., 2016). One possible explanation is that in clinical samples this differential gender effect disappears, as there is greater demand for care among men who perceive greater dysphoria (greater level of unease in order to request assistance), which could be connected with a proportional increase in ideation. Age, occupation, marital status and level of education were likewise not significantly linked to any increased presence of suicide ideation, contradicting the indications of some studies (Bennardi et al., 2017; Gradus et al., 2020; Lee et al., 2018). However, living alone was related to a significantly greater presence of ideation, since 55% of people living alone revealed this, as opposed to 28.7% of those who lived with other people.
From a clinical perspective, and also contrary to expectations (Pacheco, 2016; Ribeiro et al., 2018), the presence of non-specific suicide ideation was not specifically and significantly linked to a diagnosis of depression, although it was greater within this diagnostic group (50% compared with 25-30% in the other categories). It is nonetheless striking that some 30% of cases with suicide ideation did not receive a diagnosis of depression, or even any specific diagnosis. This would seem to indicate the horizontal nature of such symptoms and that professionals should not only focus on a cluster of patients for more in-depth evaluation and treatment. Other clinical indicators, such as the presence of personal history and consumption of psychopharmaceuticals, were in fact specifically related to the presence of suicide ideation. These indicators suggest that problems with a lengthy development and various attempted solutions are linked to greater hopelessness and unease, and ultimately a higher probability of suicide ideation. In fact, the group with suicide ideation revealed higher indices of hopelessness (65.7% versus 34.6%) and higher scores for symptoms of depression (28.88 versus 17.37 points) compared with the group without suicide ideation. This figure is consistent with previous literature, establishing a clear relationship between unease, symptoms of depression and the presence of suicide ideation, indicating hopelessness as a central process (Sueki, 2020).
As recommended by Franklin et al. (2017), the need is to conceptualise all possible factors related to suicide ideation in combination. This study identified, by means of a binary logistical model stratified into three models, that living alone is a clear and stable predictor of suicide ideation, with an OR of 4.035, representing a 4-fold increase in the probability of revealing suicide ideation. In the first model, living alone and the presence of a personal history (OR = 3.105) served to explain 19.5% of the variance in the presence of ideation. As one would expect, the inclusion within the second model of symptoms of depression and presence of hopelessness increased the explained variance to 42.5%. It is striking that living alone not only remained a predictor but increased its predictive capacity (OR = 4.727). Lastly, when one considers diagnosis, the aforementioned predictors remain significant (and the predictive capacity of living alone even continued to increase, raising the probability of the presence of suicide ideation by a factor of more than 5.6). However, the diagnosis did not prove a significant predictor. The final model finally explained 44.3% of the variance, although its increase was not statistically significant compared to the second model.
While symptoms of depression and hopelessness are clear predictive factors of suicide ideation, factors such as the presence of a personal history related to mental health may constitute a significant "attrition" effect to be taken into account. The cohabitation factor is also particularly relevant. Social support is important and fundamental in mental health, and specifically in relation to suicidal behaviour, among both an adult and a child/juvenile population (Mackin et al., 2017). Living alone may be, far from a choice, a reflection of this lack of support. It should also be borne in mind that this variable proved a significant predictor after controlling for others that could be exerting influence, such as age, marital status, and even diagnosis and symptoms of depression.
This paper is limited by its use of samples in a university setting. However, previous studies have indicated that such samples are analogous in terms of characteristics and problems with those of any outpatient centre offering psychotherapy services (Labrador et al., 2010). This is due to the fact that, though it is a university-based teaching clinic, the psychological care provided is aimed at general population, not exclusively for university students.
Another limitation, due to the archival nature of the study, was the measurement instruments used to assess the variables. Except for variables of a psychometric nature, many of the sociodemographic and clinical variables are measured through an ad hoc questionnaire, losing relevant data on the self-assessment of these variables and their depth. For example, the impact on emotional well-being of the presence of family psychological history is different if the latter is related to suicidal behaviour (family suicidal environment) rather than the presence of other psychological difficulties, or the participants' unawareness about family history does not mean it did not exist.
On the other hand, it would have been necessary to use a scale, such as the Columbia-Suicide Severity Rating Scale (C-SSRS; Posner et al., 2011) that not only measured the presence of suicidal ideation, but also independently assessed other components of suicidal continuum (wish to die, planning or intention), intensity of ideation (frequency, duration, controllability...), lifetime suicide attempts/ideation and, as well, a specific questionnaire to assess hopelessness.
Another limitation of the study with respect to clinical diagnoses is that, even though all psychologists had specific training and were supervised in the preparation of psychological reports, interrater reliability was not assessed, so the conclusions regarding the lack of relationship between suicidal ideation and diagnosis may not be reliable estimates. Likewise, it might be interesting to assess subclinical symptomatology (do not meet all the diagnostic criteria) to explore the direction of suicidal ideation in these patients.
Although it is important to emphasize that this design does not allow us to establish causal relationships, but rather associations between the variables under study, the data are robust. It would seem clear that professionals should systematically emphasize this phenomenon, conducting evaluations and, where applicable, interventions beyond symptoms of depression, unease, and of course an individual's diagnosis. It is also seen to be of relevance to continue exploring this phenomenon in greater depth within the context of healthcare, addressing the entire morbidity and building predictive and explanatory models, taking suicide ideation as the first step in a continuum which may culminate in attempted or effected suicide.
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